共查询到20条相似文献，搜索用时 31 毫秒
1.
In the last few years, the use of mathematical models in WasteWater Treatment Plant (WWTP) processes has become a common way to predict WWTP behaviour. However, mathematical models generally demand advanced input for their implementation that must be evaluated by an extensive data-gathering campaign, which cannot always be carried out. This fact, together with the intrinsic complexity of the model structure, leads to model results that may be very uncertain. Quantification of the uncertainty is imperative. However, despite the importance of uncertainty quantification, only few studies have been carried out in the wastewater treatment field, and those studies only included a few of the sources of model uncertainty. Seeking the development of the area, the paper presents the uncertainty assessment of a mathematical model simulating biological nitrogen and phosphorus removal. The uncertainty assessment was conducted according to the Generalised Likelihood Uncertainty Estimation (GLUE) methodology that has been scarcely applied in wastewater field. The model was based on activated-sludge models 1 (ASM) and 2 (ASM2). Different approaches can be used for uncertainty analysis. The GLUE methodology requires a large number of Monte Carlo simulations in which a random sampling of individual parameters drawn from probability distributions is used to determine a set of parameter values. Using this approach, model reliability was evaluated based on its capacity to globally limit the uncertainty. The method was applied to a large full-scale WWTP for which quantity and quality data was gathered. The analysis enabled to gain useful insights for WWTP modelling identifying the crucial aspects where higher uncertainty rely and where therefore, more efforts should be provided in terms of both data gathering and modelling practises. 相似文献
2.
The identifiability of parameters in a water quality model of the Biebrza River, Poland 总被引：1，自引：0，他引：1
The identifiability of model parameters of a steady state water quality model of the Biebrza River and the resulting variation in model results was examined by applying the Monte Carlo method which combines calibration, identifiability analysis, uncertainty analysis, and sensitivity analysis. The water quality model simulates the steady state concentration profiles of chloride, phosphate, ammonium, and nitrate as a function of distance along a river. The water quality model with the best combination of parameter values simulates the observed concentrations very well. However, the range of possible modelled concentrations obtained for other more or less equally eligible combinations of parameter values is rather wide. This range in model outcomes reflects possible errors in the model parameters. Discrepancies between the range in model outcomes and the validation data set are only caused by errors in model structure, or (measurement) errors in boundary conditions or input variables. In this sense the validation procedure is a test of model capability, where the effects of calibration errors are filtered out. It is concluded that, despite some slight deviations between model outcome and observations, the model is successful in simulating the spatial pattern of nutrient concentrations in the Biebrza River. 相似文献
3.
ABSTRACTReliable simulations of hydrological models require that model parameters are precisely identified. In constraining model parameters to small ranges, high parameter identifiability is achieved. In this study, it is investigated how precisely model parameters can be constrained in relation to a set of contrasting performance criteria. For this, model simulations with identical parameter samplings are carried out with a hydrological model (SWAT) applied to three contrasting catchments in Germany (lowland, mid-range mountains, alpine regions). Ten performance criteria including statistical metrics and signature measures are calculated for each model simulation. Based on the parameter identifiability that is computed separately for each performance criterion, model parameters are constrained to smaller ranges individually for each catchment. An iterative repetition of model simulations with successively constrained parameter ranges leads to more precise parameter identifiability and improves model performance. Based on these results, a more consistent handling of model parameters is achieved for model calibration. 相似文献
4.
M. van Der Perk 《水文研究》1998,12(5):683-699
A method that combines calibration and identifiability analysis of a dynamic water quality model to evaluate the relative importance of various processes affecting the dynamic aspects of water composition is illustrated by a study of the response of suspended sediment and dissolved nutrients to a flood hydrograph in a rural catchment area in the Netherlands. Since the water quality model simulates the observed concentrations of suspended sediment and dissolved nutrients reasonably well, the most important processes during the observed flood hydrograph could be determined. These were erosion, exchange between dissolved phase and bed sediments and denitrification. It is concluded that the method is very useful for identifying the most significant model parameters and processes that are essential for water quality modelling. © 1998 John Wiley & Sons, Ltd. 相似文献
5.
A simple phosphorus (P) transfer model of the Welland catchment, UK, is evaluated against multiple objective functions using a Monte Carlo approach that combines calibration, identifiability, sensitivity and uncertainty analysis. The model is based on simple conceptual rainfall‐runoff and river routing components, combined with estimates of the daily non‐point source load derived from annual landuse‐based export coefficients, disaggregated as a function of the runoff. The model has limited data requirements, consistent with data availability, and is parsimoneous with respect to the number of parameters identified through inverse modelling. The best performing parameter sets capture the main aspects of the observed flow and total P (TP) concentrations and provide a suitable basis for a decision‐support tool. However, a trade‐off is evident between matching the observed flow peaks, flow recessions and TP concentrations simultaneously, highlighting some limitations of the model structure and/or calibration data. Model analysis indicates that daily non‐point source load cannot be described as a function of near‐surface runoff and land use alone, but that other influences, including seasonality, are important. However, further model development to improve performance is likely to introduce additional complexity (in terms of parameter numbers), and hence additional problems of parameter identifiability and output uncertainty, which in turn raises issues of the information content of the available data. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
6.
The subject of environmental engineering is currently of great interest. Field experiments as well as numerical models have proven their worth in this research field. An introduction to hydrodynamic modelling, coupled to the modelling of vegetation biomass is described. The developed Strive (STream RIVer Ecosystem) model is set up in the Femme (‘Flexible Environment for Mathematically Modelling the Environment’) environment and has already proven its worth in a large number of calculations (De Doncker et al., 2006 , 2008b ). Discharges and water levels are modelled together with modelling of electrical conductivity (EC). Extensive measurement campaigns are carried out to collect a large number of observations and calibration of the model is based on this data set. Furthermore, calibration methods and the discussion of this process are displayed. As a result, it is seen that the developed Strive model can model both, hydrodynamic and ecological processes, in an accurate way. The work highlights the importance of detailed determination of Manning's coefficient, dependent on discharge and amount of biomass, as an important calibration parameter for accurate modelling. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
7.
In this study, a methodology for clustering 18 lakes in Alberta, Canada using the data of 19 water quality parameters for a period of 11 years (1988–2002) is presented. The methods consist of (i) principal component analysis (PCA) to determine the dominant water quality parameters, (ii) cluster analysis techniques to develop the characteristics of the clusters, and (iii) pattern‐match lakes to determine the appropriate cluster for each of the lakes. The PCA revealed that three principal components (PCs) were able to explain ～88% of the variability and the dominant water quality parameters were total dissolved solids, total phosphorus, and chlorophyll‐a. We obtained five clusters for the period 1994–1997 by using the dominant parameters with water quality deteriorating as the cluster number increased from 1 to 5. Upon matching cluster patterns with the entire dataset, it was observed that some of the lakes belonged to the same cluster all the time (e.g., cluster 1 for lakes Elkwater, Gregg, and Jarvis; cluster 3 for Sturgeon; cluster 4 for Moonshine; and cluster 5 for Saskatoon), while others changed with time. This methodology could be applied in other regions of the world to identify the most suitable source waters and prioritize their management. It could be helpful to analyze the natural controlling processes, pollution types, impact of seasonal changes and overall quality of source waters. This methodology could be used for monitoring water bodies in a cost effective and efficient way by sampling only less number of dominant parameters instead of using a large set of parameters. 相似文献
8.
Sean E. Walker Leonard R. Pasion Douglas W. Oldenburg Stephen D. Billings 《Journal of Applied Geophysics》2007,61(3-4):254-278
Using field data and numerical simulations we investigate the effect of data quality on time domain electromagnetic discrimination. Data quality decreases when measurements contain responses not accounted for by our mathematical modelling. This can include instrument noise, inaccurately reported position and orientation information, geologic contributions to the signal, and loss of validity of the forward modelling. Survey design is critical to data quality in order to have sufficient sampling of data anomalies, and also to ensure that each target is illuminated such that both the axial and transverse components of the polarization can be excited and measured. For dipole model based discrimination algorithms, success is contingent upon the accuracy with which the components of the polarization tensor can be estimated. Field data from different survey modes are analysed to identify noise sources and provide quantitative estimates of the noise in each survey. Inversion results show that increased noise levels lead to greater spread in recovered parameters. Monte Carlo simulations are performed in order to investigate the importance of other data quality factors. Analysis of inversion results from the simulations show that anomaly size, signal to noise ratio, positioning error, line spacing and station spacing all play a role in the spread of recovered parameters. Through the analysis of our simulation results we propose a figure of merit as a means of quantifying different data quality factors with a single number and relate this number to the accuracy with which parameters can be estimated. 相似文献
9.
Richard E. Brazier Keith J. Beven Steven G. Anthony John S. Rowan 《地球表面变化过程与地形》2001,26(12):1333-1352
An integrated modelling approach (MIRSED) which utilizes the process‐based soil erosion model WEPP (Water Erosion Prediction Project) is presented for the assessment of hillslope‐scale soil erosion at five sites throughout England and Wales. The methodology draws upon previous uncertainty analysis of the WEPP hillslope soil erosion model by the authors to qualify model results within an uncertainty framework. A method for incorporating model uncertainty from a range of sources is discussed as a first step towards using and learning from results produced through the GLUE (Generalized Likelihood Uncertainty Estimation) technique. Results are presented and compared to available observed data, which illustrate that levels of uncertainty are significant and must be taken into account if a meaningful understanding of output from models such as WEPP is to be achieved. Furthermore, the collection of quality, observed data is underlined for two reasons: as an essential tool in the development of soil erosion modelling and also to allow further constraint of model uncertainty. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
10.
Predicting seasonal and hydro-meteorological impact in environmental variables modelling via Kalman filtering 总被引：1，自引：1，他引：0
A. Manuela Gonçalves Marco Costa 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(5):1021-1038
This study focuses on the potential improvement of environmental variables modelling by using linear state-space models, as an improvement of the linear regression model, and by incorporating a constructed hydro-meteorological covariate. The Kalman filter predictors allow to obtain accurate predictions of calibration factors for both seasonal and hydro-meteorological components. This methodology can be used to analyze the water quality behaviour by minimizing the effect of the hydrological conditions. This idea is illustrated based on a rather extended data set relative to the River Ave basin (Portugal) that consists mainly of monthly measurements of dissolved oxygen concentration in a network of water quality monitoring sites. The hydro-meteorological factor is constructed for each monitoring site based on monthly precipitation estimates obtained by means of a rain gauge network associated with stochastic interpolation (kriging). A linear state-space model is fitted for each homogeneous group (obtained by clustering techniques) of water monitoring sites. The adjustment of linear state-space models is performed by using distribution-free estimators developed in a separate section. 相似文献
11.
Jurate Kriauciuniene Darius Jakimavicius Diana Sarauskiene Tadas Kaliatka 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(4):769-784
Particular attention is given to the reliability of hydrological modelling results. The accuracy of river runoff projection depends on the selected set of hydrological model parameters, emission scenario and global climate model. The aim of this article is to estimate the uncertainty of hydrological model parameters, to perform sensitivity analysis of the runoff projections, as well as the contribution analysis of uncertainty sources (model parameters, emission scenarios and global climate models) in forecasting Lithuanian river runoff. The impact of model parameters on the runoff modelling results was estimated using a sensitivity analysis for the selected hydrological periods (spring flood, winter and autumn flash floods, and low water). During spring flood the results of runoff modelling depended on the calibration parameters that describe snowmelt and soil moisture storage, while during the low water period—the parameter that determines river underground feeding was the most important. The estimation of climate change impact on hydrological processes in the Merkys and Neris river basins was accomplished through the combination of results from A1B, A2 and B1 emission scenarios and global climate models (ECHAM5 and HadCM3). The runoff projections of the thirty-year periods (2011–2040, 2041–2070, 2071–2100) were conducted applying the HBV software. The uncertainties introduced by hydrological model parameters, emission scenarios and global climate models were presented according to the magnitude of the expected changes in Lithuanian rivers runoff. The emission scenarios had much greater influence on the runoff projection than the global climate models. The hydrological model parameters had less impact on the reliability of the modelling results. 相似文献
12.
13.
Seismic driven probabilistic classification of reservoir facies for static reservoir modelling: a case history in the Barents Sea 总被引：2，自引：0，他引：2
Dario Grana Enrico Paparozzi Silvia Mancini Cristiano Tarchiani 《Geophysical Prospecting》2013,61(3):613-629
In this paper we present a case history of seismic reservoir characterization where we estimate the probability of facies from seismic data and simulate a set of reservoir models honouring seismically‐derived probabilistic information. In appraisal and development phases, seismic data have a key role in reservoir characterization and static reservoir modelling, as in most of the cases seismic data are the only information available far away from the wells. However seismic data do not provide any direct measurements of reservoir properties, which have then to be estimated as a solution of a joint inverse problem. For this reason, we show the application of a complete workflow for static reservoir modelling where seismic data are integrated to derive probability volumes of facies and reservoir properties to condition reservoir geostatistical simulations. The studied case is a clastic reservoir in the Barents Sea, where a complete data set of well logs from five wells and a set of partial‐stacked seismic data are available. The multi‐property workflow is based on seismic inversion, petrophysics and rock physics modelling. In particular, log‐facies are defined on the basis of sedimentological information, petrophysical properties and also their elastic response. The link between petrophysical and elastic attributes is preserved by introducing a rock‐physics model in the inversion methodology. Finally, the uncertainty in the reservoir model is represented by multiple geostatistical realizations. The main result of this workflow is a set of facies realizations and associated rock properties that honour, within a fixed tolerance, seismic and well log data and assess the uncertainty associated with reservoir modelling. 相似文献
14.
Clay‐settling areas (CSAs) are one of the most conspicuous and development‐limiting landforms remaining after phosphate mining. Many questions are asked by the mining and regulatory communities with regard to the correct modelling (predictive) methods and assumptions that should be used to yield viable hydrologic post‐reclamation landforms within CSAs. Questions as to the correct methodology to use in modelling/predicting long‐term CSA hydrologic performance have historically been difficult to answer because the data and analysis to support popular hypotheses did not exist. The goal of this paper was to substantially improve the data, analysis and predictive methodology necessary to return CSAs to viable hydrologic units, and moreover, to develop better understanding of the hydrology of CSAs and their ability to support wetlands. The study site is located at the Fort Meade Mine in Polk County, Florida. In this paper, continuous model simulation and calibration of study site were conducted for the hydrologic model, Hydrological Simulation Program – FORTRAN, which was generally selected on the basis of its popularity in predicting the hydrologic behaviour of CSAs. The objective of this study was to simulate streamflow discharges and stage to estimate runoff response from these areas on the basis of the observed rainfall within the CSA. A set of global hydrologic parameters was selected and tested during the calibration by the parameter estimation software PEST. A comparison of the simulated and observed flow data indicates that the model calibration adequately reproduces the hydrologic response of the CSAs. The estimated parameters can be used as references for future application of the model. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
15.
Allogenic karst systems function in a particular way that is influenced by the type of water infiltrating through river water losses, by karstification processes, and by water quality. Management of this system requires a good knowledge of its structure and functioning, for which a new methodology based on an inverse modeling approach appears to be well suited. This approach requires both spring and river inflow discharge measurements and a continuous record of chemical parameters in the river and at the spring. The inverse model calculates unit hydrographs and the impulse responses of fluxes from rainfall hydraulic head at the spring or rainfall flux data, the purpose of which is hydrograph separation. Hydrograph reconstruction is done using rainfall and river inflow data as model input and enables definition at each time step of the ratio of each component. Using chemical data, representing event and pre-event water, as input, it is possible to determine the origin of spring water (either fast flow through the epikarstic zone or slow flow through the saturated zone). This study made it possible to improve a conceptual model of allogenic karst system functioning. The methodology is used to study the Bas-Agly and the Cent Font karst systems, two allogenic karst systems in Southern France. 相似文献
16.
In order to predict the behaviour of plumes from three deep ocean outfalls for sewage off Sydney, three-dimensional numerical modelling was used. The modelling suite was driven by data generated by an oceanographic monitoring station measuring wind, ocean currents, temperature and wave characteristics. Three different modelling phases are implemented daily, a nearfield model, a hydrodynamic model and a water quality model. Model output can be used by the New South Wales Environment Protection Authority to predict water quality at ocean beaches and inform the community. 相似文献
17.
Robert L. Wilby 《水文研究》2005,19(16):3201-3219
Despite their acknowledged limitations, lumped conceptual models continue to be used widely for climate‐change impact assessments. Therefore, it is important to understand the relative magnitude of uncertainties in water resource projections arising from the choice of model calibration period, model structure, and non‐uniqueness of model parameter sets. In addition, external sources of uncertainty linked to choice of emission scenario, climate model ensemble member, downscaling technique(s), and so on, should be acknowledged. To this end, the CATCHMOD conceptual water balance model was used to project changes in daily flows for the River Thames at Kingston using parameter sets derived from different subsets of training data, including the full record. Monte Carlo sampling was also used to explore parameter stability and identifiability in the context of historic climate variability. Parameters reflecting rainfall acceptance at the soil surface in simpler model structures were found to be highly sensitive to the training period, implying that climatic variability does lead to variability in the hydrologic behaviour of the Thames basin. Non‐uniqueness of parameters for more complex model structures results in relatively small variations in projected annual mean flow quantiles for different training periods compared with the choice of emission scenario. However, this was not the case for subannual flow statistics, where uncertainty in flow changes due to equifinality was higher in winter than summer, and comparable in magnitude to the uncertainty of the emission scenario. Therefore, it is recommended that climate‐change impact assessments using conceptual water balance models should routinely undertake sensitivity analyses to quantify uncertainties due to parameter instability, identifiability and non‐uniqueness. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
18.
This paper presents a method of identification for determining non-linear dynamic models for certain hysteretic structures. Particular attention is given to modelling and identifying the hysteretic behaviour of structures from strong-motion earthquake data. In this method, the response is separated into mode-like components which are analogous to those of a linear system. Based on modelling of the generalized restoring force of each mode-like component, both non-hysteretic and hysteretic non-linear models are incorporated into the general methodology. A non-hysteretic model provides an initial estimate for a final hysteretic model. The approach is applicable even when data are available from only a small number of locations in the structure. The structural model identified from this method provides a means to predict the response to future events and, ultimately, to examine the damage to a structure as a result of an earthquake. 相似文献
19.
Using experimental data to reduce the single-building sigma of fragility curves: case study of the BRD tower in Bucharest, Romania 总被引：1，自引：0，他引：1
Matthieu Perrault Philippe Gueguen Alexandru Aldea Sorin Demetriu 《地震工程与工程振动(英文版)》2013,12(4):643-658
The lack of knowledge concerning modelling existing buildings leads to significant variability in fragility curves for single or grouped existing buildings. This study aims to investigate the uncertainties of fragility curves, with special consideration of the single-building sigma. Experimental data and simplified models are applied to the BRD tower in Bucharest, Romania, a RC building with permanent instrumentation. A three-step methodology is applied： （1） adjustment of a linear MDOF model for experimental modal analysis using a Timoshenko beam model and based on Anderson＇s criteria, （2） computation of the structure＇s response to a large set of accelerograms simulated by SIMQKE software, considering twelve ground motion parameters as intensity measurements （IM）, and （3） construction of the fragility curves by comparing numerical interstory drift with the threshold criteria provided by the Hazus methodology for the slight damage state. By introducing experimental data into the model, uncertainty is reduced to 0.02 considering Sd ） as seismic intensity IM and uncertainty related to the model is assessed at 0.03. These values must be compared with the total uncertainty value of around 0.7 provided by the Hazus methodology. 相似文献
20.
Development of a modelling methodology for simulation of long-term morphological evolution of the southern Baltic coast 总被引：1，自引：1，他引：0
The Darss–Zingst peninsula at the southern Baltic Sea is a typical wave-dominated barrier island system which includes an
outer barrier island and an inner lagoon. The formation of the Darss–Zingst peninsula dates back to the Littorina Transgression
onset about 8,000 cal BP. It originated from several discrete islands, has been reshaped by littoral currents, wind-induced
waves during the last 8,000 years and evolved into a complex barrier island system as today; thus, it may serve as an example
to study the coastal evolution under long-term climate change. A methodology for developing a long-term (decadal-to-centennial)
process-based morphodynamic model for the southern Baltic coastal environment is presented here. The methodology consists
of two main components: (1) a preliminary analysis of the key processes driving the morphological evolution of the study area
based on statistical analysis of meteorological data and sensitivity studies; (2) a multi-scale high-resolution process-based
model. The process-based model is structured into eight main modules. The two-dimensional vertically integrated circulation
module, the wave module, the bottom boundary layer module, the sediment transport module, the cliff erosion module and the
nearshore storm module are real-time calculation modules which aim at solving the short-term processes. A bathymetry update
module and a long-term control function set, in which the ‘reduction’ concepts and technique for morphological update acceleration
are implemented, are integrated to up-scale the effects of short-term processes to a decadal-to-centennial scale. A series
of multi-scale modelling strategies are implemented in the application of the model to the research area. Successful hindcast
of the coastline change of the Darss–Zingst peninsula for the last 300 years validates the modelling methodology. Model results
indicate that the coastline change of the Darss–Zingst peninsula is dominated by mechanisms acting on different time scales.
The coastlines of Darss and the island of Hiddensee are mainly reshaped by long-term effects of waves and longshore currents,
while the coastline change of the Zingst peninsula is due to a combination of long-term effects of waves and short-term effects
caused by wind storms. 相似文献